Automated, schedule-based validation and cleaning of meter data for meter-to-bill process
Intelligent validation, estimation and editing of measurement data combined
with big data analytics for all utilities


Real time detection of anomalies and predictions based on configurable rules and analytical models operating on current and historical data

Increase your meter-to-bill efficiency
Automated process of cleaning measurement data address all meter data issues before billing cycle and minimize compliant costs. You can identify missing reading data, provide right consumption data estimation and filling in the data to achieve their consistency for billing process and further analysis
Minimize anomalies and prevent from frauds
You can detect right anomalies early and analyze if it is meter malfunction only or potential theft, you can turn your field resources from schedule-based into event-based workforce management and react only on positive alerts
Increase the accuracy of forecasts of consumption and demand
Higher quality of meter data with full history of meter readings combined with operational insights gives you the opportunity to make real consumption and demand forecast for all of your network or particular customer
Hit the ground running with our flexible delivery and cooperation model. You choose the option that’s best for you. We also recommend you check out our Data Science consultancy services to assure top quality meter data and discover how Smartvee can solve issues that could be affecting your business.

Ready-to-use cloud service providing all the features you’re looking for, including meter data import and export, vee process, analysis, reporting and data visualization in a simple subscription model with a try-and-buy period.

Ready-to-use private cloud application allowing customization and integration with your existing solutions without having to deploy it into your infrastructure

Deeper integration with your infrastructure and customization to your particular requirements, especially in the field of analytical models and reporting